Exploratory Analysis

Sparse Exploratory Factor Analysis.

Sparse principal component analysis is a very active research area in the last decade. It produces component loadings with many zero entries which facilitates their interpretation and helps avoid redundant variables. The classic factor analysis is another popular dimension reduction technique which shares similar interpretation problems and could greatly benefit from sparse solutions. Unfortuna...

Exploratory data analysis

Bayesian Exploratory Factor Analysis.

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bay...

Exploratory Correlation Analysis

We present a novel unsupervised artificial neural network for the extraction of common features in multiple data sources. This algorithm, which we name Exploratory Correlation Analysis (ECA), is a multi-stream extension of a neural implementation of Exploratory Projection Pursuit (EPP) and has a close relationship with Canonical Correlation Analysis (CCA). Whereas EPP identifies ”interesting” s...

Exploratory Multivariate Data Analysis

Cover The words on the front and back cover pages have been ordered by letting MATLAB ® choose randomly and uniformly from a list of selected keywords. i Preface This PhD dissertation is based on a series of research projects conducted at The Royal Veterinary and Agricultural University (KVL), in the Chemometrics Research Group of Professor Lars Munck and colleagues during the period 1996-99. P...